tabnet #205
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tabnet #205
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you-n-g
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Jan 21, 2021
| @@ -25,6 +25,7 @@ The numbers shown below demonstrate the performance of the entire `workflow` of | |||
| | XGBoost (Tianqi Chen, et al.) | Alpha158 | 0.0481±0.00 | 0.3659±0.00| 0.0495±0.00 | 0.4033±0.00 | 0.1111±0.00 | 1.2915±0.00| -0.0893±0.00 | | |||
| | LightGBM (Guolin Ke, et al.) | Alpha158 | 0.0475±0.00 | 0.3979±0.00| 0.0485±0.00 | 0.4123±0.00 | 0.1143±0.00 | 1.2744±0.00| -0.0800±0.00 | | |||
| | MLP | Alpha158 | 0.0358±0.00 | 0.2738±0.03| 0.0425±0.00 | 0.3221±0.01 | 0.0836±0.02 | 1.0323±0.25| -0.1127±0.02 | | |||
| | TabNet with pretrain (Sercan O. Arikm et al) | Alpha158 | 0.0344±0.00|0.205±0.11|0.0398±0.00 |0.3479±0.01|0.0827±0.02|1.1141±0.32 |-0.0925±0.02 | | |||
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How many times did you train the model to get this result?
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I trained it three times with different random seeds
qlib/contrib/model/pytorch_tabnet.py
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| from ...data.dataset.handler import DataHandlerLP | ||
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| class TabNet_Model(Model): |
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Under in class is not the preferred naming rules
https://github.com/amontalenti/elements-of-python-style#preferred-naming-rules
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@javaThonc |
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Aug 16, 2025
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updating Tabnet model and its performance on Alpha 158